{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dagstermill"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "from dagster import ModeDefinition, ResourceDefinition\n",
    "from collections import namedtuple\n",
    "\n",
    "url = 'postgresql://{username}:{password}@{hostname}:5432/{db_name}'.format(\n",
    "    username='test', password='test', hostname='localhost', db_name='test'\n",
    ")\n",
    "DbInfo = namedtuple('DbInfo', 'url')\n",
    "context = dagstermill.get_context(\n",
    "    mode_def=ModeDefinition(\n",
    "        resource_defs={'db_info': ResourceDefinition(lambda _: DbInfo(url))}\n",
    "    )\n",
    ")\n",
    "\n",
    "table_name = 'average_sfo_outbound_avg_delays_by_destination'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "db_url = context.resources.db_info.url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import sqlalchemy as sa\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "from dagster.utils import mkdir_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/max/.virtualenvs/dagster/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "engine = sa.create_engine(db_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "plots_path = os.path.join(os.getcwd(), 'plots')\n",
    "mkdir_p(plots_path)\n",
    "pdf_path = os.path.join(plots_path, 'sfo_delays_by_destination.pdf')\n",
    "pp = PdfPages(pdf_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "delays = pd.read_sql('select * from {table_name}'.format(table_name=table_name), engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>arrival_delay</th>\n",
       "      <th>departure_delay</th>\n",
       "      <th>origin</th>\n",
       "      <th>destination</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>SFO</td>\n",
       "      <td>EUG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-4.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>SFO</td>\n",
       "      <td>BOS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SFO</td>\n",
       "      <td>SAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-22.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>SFO</td>\n",
       "      <td>MCO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-3.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>SFO</td>\n",
       "      <td>LAS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   arrival_delay  departure_delay origin destination\n",
       "0           10.0             16.0    SFO         EUG\n",
       "1           -4.0             -5.0    SFO         BOS\n",
       "2           13.0              0.0    SFO         SAN\n",
       "3          -22.0             -1.0    SFO         MCO\n",
       "4           -3.0             -4.0    SFO         LAS"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delays.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/max/.virtualenvs/dagster/lib/python3.6/site-packages/numpy/lib/histograms.py:754: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "/Users/max/.virtualenvs/dagster/lib/python3.6/site-packages/numpy/lib/histograms.py:755: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(delays['arrival_delay'], bins=100)\n",
    "plt.title('Flight Delays (Origin SFO)')\n",
    "plt.xlabel('Delay at Arrival (Minutes)')\n",
    "plt.ylabel('Number of Flights')\n",
    "pp.savefig()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(delays['departure_delay'], delays['arrival_delay'], alpha=.05)\n",
    "plt.plot([-100,1400], [-100,1400], 'k:', alpha=0.75)\n",
    "plt.title('Flight Delays (Origin SFO)')\n",
    "plt.xlabel('Delay at Departure (Minutes)')\n",
    "plt.ylabel('Delay at Arrival (Minutes)')\n",
    "pp.savefig()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    44011.000000\n",
       "mean         3.521801\n",
       "std         14.436305\n",
       "min       -123.000000\n",
       "25%         -4.000000\n",
       "50%          5.000000\n",
       "75%         12.000000\n",
       "max         65.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(delays['departure_delay'] - delays['arrival_delay']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "departure_delays_by_destination = delays.groupby('destination').mean()['departure_delay']\n",
    "arrival_delays_by_destination = delays.groupby('destination').mean()['arrival_delay']\n",
    "n_flights_by_destination = delays.groupby('destination').count()['origin']\n",
    "\n",
    "import math\n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "# ax.scatter(\n",
    "#     departure_delays_by_destination,\n",
    "#     arrival_delays_by_destination,\n",
    "#     s=n_flights_by_destination.map(math.sqrt),\n",
    "#     alpha=0.5\n",
    "# )\n",
    "plt.xlim(0, 25)\n",
    "plt.ylim(-5, 20)\n",
    "plt.plot([-5,20], [-5,20], 'k-', alpha=0.5)\n",
    "\n",
    "\n",
    "for i, destination in enumerate(n_flights_by_destination.index):\n",
    "    departure_delay = departure_delays_by_destination[i]\n",
    "    arrival_delay = arrival_delays_by_destination[i]\n",
    "    n_flights = n_flights_by_destination[i]\n",
    "    if (departure_delay > 0 and departure_delay < 25 and arrival_delay > -25 and departure_delay < 25 and n_flights > 500):\n",
    "        arrow_width = math.sqrt(n_flights/15000)\n",
    "        arrow_head_width = 2 * arrow_width\n",
    "        arrow_head_length = arrow_width\n",
    "        improved = (arrival_delay - departure_delay) < 0\n",
    "        annotation_y = arrival_delay + 0.3 if not improved else (arrival_delay - 0.3)\n",
    "        ax.arrow(\n",
    "            departure_delay,\n",
    "            departure_delay,\n",
    "            0,\n",
    "            arrival_delay - departure_delay,\n",
    "            width=arrow_width,\n",
    "            head_length=arrow_head_length,\n",
    "            head_width=arrow_head_width,\n",
    "            alpha=0.5,\n",
    "            length_includes_head=True)\n",
    "        ax.annotate(\n",
    "            destination,\n",
    "            (departure_delay, annotation_y),\n",
    "            horizontalalignment='center',\n",
    "            verticalalignment=('top' if improved else 'bottom'))\n",
    "\n",
    "plt.title('Flight Delays (SFO to Destinations with > 500 Q2 Departures')\n",
    "plt.xlabel('Average Delay at Departure by Destination (Minutes)')\n",
    "plt.ylabel('Average Delay at Arrival by Destination (Minutes)')\n",
    "pp.savefig()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "pp.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/max/dev/dagster/python_modules/airline-demo/airline_demo/notebooks/plots/sfo_delays_by_destination.pdf'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dagster import LocalFileHandle\n",
    "dagstermill.yield_result(LocalFileHandle(pdf_path))"
   ]
  }
 ],
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